Verified75% confidenceFactExact time
The Latent Diffusion Model was proposed by Rombach et al. in 2022, combining the diffusion process with the latent space of a VAE, reducing the computational dimensions from 512×512×3 to 64×64×4.
5
Sources
75%
Confidence
Long-term
Relevance
8/6/2026
First Seen
Sources
Midjourney中世纪场景Prompt技巧拆解与实战指南
Related Claims
UnverifiedLatent Diffusion reduced the computational load by several orders of magnitude in 2022 by operating in latent space.77% similarUnverifiedIn 2021, Robin Rombach and others from Ludwig Maximilian University of Munich proposed the Latent Diffusion Model (LDM), which uses a pre-trained VAE to compress images into a low-dimensional latent space (typically 1/8 of the original resolution) before performing diffusion denoising.75% similarUnverifiedThe 2020 DDPM paper laid the foundation for modern diffusion models, after which Latent Diffusion Models significantly reduced computational costs by performing the diffusion process in a compressed latent space.74% similarVerifiedStable Diffusion compresses the diffusion process from pixel space to latent space, implemented by a Variational Autoencoder (VAE).72% similarUnverifiedVariational autoencoders (VAEs) and diffusion models rely on sampling from probability distributions in latent space.70% similar
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